Iannuccelli Marta, Lo Surdo Prisca, Licata Luana, Castagnoli Luisa, Cesareni Gianni, Perfetto Livia
Department of Biology, University of Rome Tor Vergata, Rome, Italy.
Fondazione Human Technopole, Milan, Italy.
Front Mol Biosci. 2022 May 18;9:893256. doi: 10.3389/fmolb.2022.893256. eCollection 2022.
Some inherited or somatically-acquired gene variants are observed significantly more frequently in the genome of cancer cells. Although many of these cannot be confidently classified as driver mutations, they may contribute to shaping a cell environment that favours cancer onset and development. Understanding how these gene variants causally affect cancer phenotypes may help developing strategies for reverting the disease phenotype. Here we focus on variants of genes whose products have the potential to modulate metabolism to support uncontrolled cell growth. Over recent months our team of expert curators has undertaken an effort to annotate in the database SIGNOR 1) metabolic pathways that are deregulated in cancer and 2) interactions connecting oncogenes and tumour suppressors to metabolic enzymes. In addition, we refined a recently developed graph analysis tool that permits users to infer causal paths leading from any human gene to modulation of metabolic pathways. The tool grounds on a human signed and directed network that connects ∼8400 biological entities such as proteins and protein complexes via causal relationships. The network, which is based on more than 30,000 published causal links, can be downloaded from the SIGNOR website. In addition, as SIGNOR stores information on drugs or other chemicals targeting the activity of many of the genes in the network, the identification of likely functional paths offers a rational framework for exploring new therapeutic strategies that revert the disease phenotype.
在癌细胞基因组中，某些遗传或体细胞获得的基因变异被观察到的频率明显更高。尽管其中许多变异不能被确定地归类为驱动突变，但它们可能有助于塑造有利于癌症发生和发展的细胞环境。了解这些基因变异如何因果性地影响癌症表型，可能有助于制定逆转疾病表型的策略。在这里，我们关注其产物有可能调节代谢以支持不受控制的细胞生长的基因变异。在最近几个月里，我们的专家策展团队致力于在SIGNOR数据库中注释：1）癌症中失调的代谢途径；2）连接癌基因和肿瘤抑制因子与代谢酶的相互作用。此外，我们改进了一种最近开发的图形分析工具，该工具允许用户推断从任何人类基因到代谢途径调节的因果路径。该工具基于一个人类有符号和有向网络，该网络通过因果关系连接约8400个生物实体，如蛋白质和蛋白质复合物。该网络基于超过30000个已发表的因果联系，可从SIGNOR网站下载。此外，由于SIGNOR存储了针对网络中许多基因活性的药物或其他化学物质的信息，识别可能的功能路径为探索逆转疾病表型的新治疗策略提供了一个合理的框架。
